• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.2
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• pp.29-36
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• 2009

The analysis of Radar signal, telecommunication, bioengineering, seismic, and acoustic signal is consist of the Non-stationary signal which has non-linear phase variation. Non-stationary signal means that the physical properties of signal depend on time variation and the instantaneous frequency represents physical property of these type of signal. Thus estimation of the instantaneous frequency of non-stationary signal is important subject in signal processing. In this work, the instantaneous frequency analysis method utilizing continuous wavelets transform is represented and compared with Hilbert Transform method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.5
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• pp.765-771
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• 2001

Elastic-plastic fracture toughness JIC can be used a s an effective design criterion in elastic-plastic fracture mechanics. Among the JIC test methods approved by ASTM, unloading compliance method was used in this study. In order to examine the relationship between fracture behavior of JIC test and AE signals, the post processing of AE signals has been carried out by Short Time Fourier Transform(STFT), one of the time-frequency analysis methods. The objective of this study is to evaluate the application of characterization of AE signals for unloading compliance method of JIC test. As a result of time-frequency analysis, we could extract the AE from the raw signal and analyze the frequencies in AE signal at the same time. AE signal generated by elastic-plastic fracture of material has some different aspects at elastic and plastic ranges, or the first portion of crack growth by fracture. First of all, increased energy recorded and detected by using AE count method increase rapidly from the start of ductile fracture. The variation of main frequency range with time-frequency analysis method could be confirmed. We could know fracture behavior of interior material by examination AE characteristics generated in real-time when elastic-plastic fracture occurred in material under loading.

• Journal of Electrical Engineering and Technology
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• v.3 no.4
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• pp.576-583
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• 2008

In this study, we attempt to design a real-time autonomic nervous system(ANS) evaluation system usable during exercise using heart instantaneous frequency(HIF). Although heart rate variability(HRV) is considered to be a representative signal widely used ANS evaluation system, the R-peak detection process must be included to obtain an HRV signal, which involves a high sampling frequency and interpolation process. In particular, it cannot accurately evaluate the ANS using HRV signals during exercise because it is difficult to detect the R-peak of electrocardiogram(ECG) signals with exposure to many noises during exercise. Therefore, in this study, we develop the ground for a system that can analyze an ANS in real-time by using the HIF signal circumventing the problem of the HRV signal during exercise. First, we compare the HRV and HIF signals in order to prove that the HIF signal is more efficient for ANS analysis than HRV signals during exercise. Further, we performed real-time ANS analysis using HIF and confirmed that the exerciser's ANS variation experiences massive surges at points of acceleration and deceleration of the treadmill(similar to HRV).

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.107-111
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• 2005

It has been reviewed whether it would be suitable that the application of the time-frequency signal analysis techniques to estimate the location of the impact source in plate structure. The STFT(Short Time Fourier Transform), WVD(Wigner-Ville distribution) and CWT(Continuous Wavelet Transform) methods are introduced and the advantages and disadvantages of those methods are described by using a simulated signal component. The essential of the above proposed techniques is to separate the traveling waves in both time and frequency domains using the dispersion characteristics of the structural waves. These time-frequency methods are expected to be more useful than the conventional time domain analyses fer the impact localization problem on a plate type structure. Also it has been concluded that the smoothed WVD can give more reliable means than the other methodologies for the location estimation in a noisy environment.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.607-610
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• 2009

The abnormal combustion in the running engine results to knocking which increases the pressure and temperature in the cylinder, thereby decreasing the generated power by reducing the thermal efficiency. When the temperature and pressure in the cylinder increased rapidly by knocking, abnormal combustion takes place and the engine power is decreased. To investigate the knocking phenomenon, accelerometers are installed in the cylinder head to monitor and diagnose the vibration signal. As method of signal analysis, the time-frequency analysis method was adapted for acquisition of vibration signal and analyzes engine combustion in the short time. In this experiment, after analyzing time data which is stored in the signal recorder in one unit work (4 strokes: 2 revolutions), the signal with frequency and Wavelet methods with extracted one engine combustion data was also analyzed. Then, normal condition with no knocking signal is analyzed at this time. Hereafter, the experiments made a standard for distinguishing normal and abnormal condition to be carried out in acquisition of vibration signal at all cylinders and extracting knocking signal. In addition, analyzing methods can be diverse with Symmetry Dot Patterns (SDP), Time Synchronous Average (TSA), Wigner-Ville Distribution (WVD), Wigner-Ville Spectrum (WVS) and Mean Instantaneous Power (MIP) in the cold test [2]. With signal processing of vibration from engine knocking sensor, the authors adapted a part of engine /rotor vibration analysis and monitoring system for marine vessels to prevent several problems due to engine knocking

• Structural Engineering and Mechanics
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• v.66 no.2
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• pp.185-193
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• 2018

In this study, low- and high-frequency structure behaviors were identified and a systematic analysis procedure was proposed using noisy GPS data from a 165-m-high tower in ${\dot{I}}stanbul$, Turkey. The raw GPS data contained long- and short-periodic position changes and noisy signals at different frequencies. To extract the significant results from this complex dataset, the general structure and components of the GPS signal were modeled and analyzed in the time and frequency domains. Uncontrolled jumps and deviations involving the signal in the time domain were pre-filtered. Then, the signal was converted to the frequency domain after applying low- and high-pass filters, and the frequency and periodic component values were calculated. The spectrum of the tower motion obtained from the filtered GPS data had dominant peaks at a low frequency of $1.15572{\times}10-4Hz$ and a high frequency of 0.16624 Hz, consistent with two equivalent GPS datasets. Then, the signal was reconstructed using inverse Fourier transform with the dominant low frequency values to obtain filtered and interpretable clean signals. With the proposed sequence, processing of noisy data collected from the GPS receivers mounted very close to the structure is effective in revealing the basic behaviors and features of buildings.

• The Journal of the Acoustical Society of Korea
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• v.17 no.4E
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• pp.41-47
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• 1998

Microphone is the first link in the speech recognition system. Depending on its type and mounting position, the microphone can significantly distort the spectrum and affect the performance of the speech recognition system. In this paper, characteristics of the speech signal for different microphones and microphone distances are investigated both in time and frequency domains. In the time domain analysis, the average signal-to-noise ration is measure ration is measured for the database we collected depending on the microphones and microphone distances. Mel-frequency spectral coefficients and mel-frequency cepstrum are computed to examine the spectral characteristics. Analysis results are discussed with our findings, and the result of recognition experiments is given.

• Journal of Biomedical Engineering Research
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• v.29 no.4
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• pp.278-285
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• 2008

In this study the complex-valued continuous wavelet transform (CWT) has been applied in detection of Electrocardiograms (ECG) as response to various signal classification methods such as Fourier transforms and other tools of time frequency analysis. Experiments have shown that CWT may serve as a detector of non-stationary signal changes as ECG. The tested signal is corrupted by short time events. We applied CWT to detect short-time event and the result image representation of the signal has showed us that one can easily find the discontinuity at the time scale representation. Analysis of ECG signal using complex-valued continuous wavelet transform is the first step to detect possible changes and alternans. In the second step, modulus and phase must be thoroughly examined. Thus, short time events in the ECG signal, and other important characteristic points such as frequency overlapping, wave onsets/offsets extrema and discontinuities even inflection points are found to be detectable. We have proved that the complex-valued CWT can be used as a powerful detector in ECG signal analysis.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.176-181
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• 2002

The continuous Gabor wavelet transform (GWT) has been utilized as a useful time-frequency analysis tool to identify the rapidly-varying characteristics of some wave signals. In the application of GWT, it is important to select the Gabor wavelet with the optimal shape factor by which the time-frequency distribution of a signal can be accurately estimated. To find the signal-dependent optimal Gabor wavelet shape factor, the notion of the Shannon entropy which mesures the extent of signal energy concentration in the time-frequency plane is employed. To verify the validity of the present entropy-based scheme, we have applied it to the time-frequency analysis of a set of elastic bending wave signals generated by an impact in a solid cylinder.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.10a
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• pp.110-114
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• 2012

We studied on the nondestructive evaluation of the elastic wave signal of SiC ceramics and SiC/SiC composite ceramics under monotonic tensile loading. The elastic wave signal of cross and unidirectional SiC/SiC composite ceramics were obtained by pencil lead method and bending test. It was applied for the time-frequency method which used by the discrete wavelet analysis algorithm. The time-frequency analysis provides time variation of each frequency component involved in a waveform, which makes it possible to evaluate the contribution of SiC fiber frequency. The results were compared with the characteristic of frequency group from SiC slurry and fiber. Based on the results, if it is possible to shift up and design as a higher frequency group, we will can make the superior material better than those of exiting SiC/SiC composites.